In this article, a robust nonlinear friction control strategy is developed using friction observer and recurrent fuzzy neural network. The adaptive dynamic friction observer based on the LuGre friction model is proposed to estimates the friction parameters and a directly immeasurable friction state variable. A RFNN approximator and reconstructed error compensator is also designed to give additional robustness to the control system due to the presence of the friction model uncertainty. A proposed composite control scheme with basic basckstepping controller is applied to the position tracking control of the servo mechanical system. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Han, S. I., Jeong, C. S., Park, S. H., Jeong, Y. M., Lee, C. D., & Yang, S. Y. (2009). Intelligent nonlinear friction compensation using friction observer and backstepping control. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5754 LNCS, pp. 826–833). https://doi.org/10.1007/978-3-642-04070-2_88
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